Trust in Automated Vehicles Fredrick Ekman and Mikael Johansson - PDF document

4/20/2018 Trust in Automated Vehicles Fredrick Ekman and Mikael Johansson ekmanfr@chalmers.se, johamik@chalmers.se Design & Human Factors, Chalmers Adoption and use of technical systems Energy systems and resource efficiency Energy systems and resource efficiency Urban mobility and transport systems Urban mobility and transport systems • users’ needs and requirements for technical systems • use and meaning of technical products and systems • prerequisites for users’ adoption of new technologies Well-being and health Well-being and health Human- machine systems (incl HMI) • interplay between human and "machine” – from simple products to complex socio-technical systems • performance, safety Sustainability and everyday life • design for sustainable behaviour • understanding behaviour and change User experience • sensing, perceiving and react to products and events • aesthetics • product identity and meaning 1

4/20/2018 Adoption and use of technical systems Energy systems and resource efficiency Urban mobility and transport systems Urban mobility and transport systems • users’ needs and requirements for technical systems • use and meaning of technical products and systems • prerequisites for users’ adoption of new technologies Well-being and health Human- machine systems (incl HMI) • interplay between human and "machine” – from simple products to complex socio-technical systems • performance, safety Sustainability and everyday life • design for sustainable behaviour • understanding behaviour and change User experience • sensing, perceiving and react to products and events • aesthetics • product identity and meaning Mikael Johansson, PhD Student Drivers’/Users’ Understanding of Automated Vehicles Fredrick Ekman, PhD Student Drivers’/Users’ Trust in Automated Vehicles 2

4/20/2018 Expert Systems • Professional Training • High degree of system understanding • Time for Consideration • Team work Automated Vehicles (AVs) Novice users • • Little training • Low system understanding • Adoption/Acceptance • Choice to adopt • Trust highly important 3

4/20/2018 Reality User’s perception of system Implications Mistrust • • Using the system in an unintended way • Accidents • Distrust • Not adopting the system 4

4/20/2018 Trust Fundamentals (Lee & See, 2004) Processing Trust (Lee & See, 2004) 5

4/20/2018 In Order to Achieve Trust (Lee & See, 2004) Factors Influencing Trust (Hoff & Bashir, 2016) 6

4/20/2018 Factors Influencing Trust Embodiment Transparency Communication style Ease of use (Hoff & Bashir, 2016) Automated Vehicle Research • “Providing user with “how and why” information regarding imminent autonomous action results in the safest driving performance but increases negative feelings in drivers.” (Koo et.al., 2015) • “Users who were provided with the uncertainty information trusted the automated system less than those who did not receive such information.” (Helldin et.al., 2013) • “Trusting smart systems depends on those systems sharing the user's goals” (Verberne et.al., 2012) • “Participants trusted that the vehicle would perform more competently as it acquired more anthropomorphic features .” (Waytz et.al., 2014) However, another study showed that anthropomorphic features had a low effect on trust. “Instead, the way in which the car manoeuvred and handled obstacles was a major carrier of trust.” (Aremyr et.al., 2018) 7

4/20/2018 Automated Vehicle Research • Graphical User Interfaces Not much focus on implicit cues • • AV driving behavior • Acceleration/Deceleration • Lane positioning Experimental Study • Does a Automated vehicle’s driving behavior affect trust? • Comparing two simulated AV driving behaviors at AstaZero with a Wizard-of-Oz-car • No graphical user interface • No secondary task 8

4/20/2018 Defensive Aggressive Starting & stopping Keep the vehicle rolling Start & stop behaviour (avoid standstill) (come to full stop) Acc./Retardation Avoid heavy acc/deacc. Heavy acc/deacc. pattern Early indicate right or left turn Indicate late right or left turn Lane positioning (through positioning in lane) (through positioning in lane) Keep longer distance Keep shorter distance Distance to object (lateral & longitudinal) (lateral & longitudinal) to other objects to other objects Study procedure • 18 participants between 20 and 55 years (50/50 male/female) • Rated trust in predetermined situations 9

4/20/2018 Meeting other car 10

4/20/2018 Results Questionnaire – Aggressive vs. Defensive 0 2 4 6 8 10 12 Def. Eco I understood how the self-driving car operated Agg. Sporty I had full confidence in the competence of the self- Def. Eco Agg. driving car Sporty Def. Eco I thought the self-driving car was safe to ride Agg. Sporty Def. Eco I could trust the self-driving car +1 Agg. Sporty >+1 Def. Eco I believe the car did what was best for me Agg. Sporty Def. Eco I thought the car's driving behaviour felt predictable Agg. Sporty Def. Eco If my car worked like this, I would let it drive by itself Agg. Sporty If my car drove by itself, the experience would be better Def. Eco than driving on my own Agg. Sporty 11

4/20/2018 Perception of the AV behaviour • Vehicle capacity (Performance) • Planned decisions • Clearly showing position in lane • No sudden actions • Smooth turns (without perceived continuous compensation) • User’s understanding of the AV’s upcoming actions (Process) • Gentle actions but distinct lane placement before situation • Coming to full stop (when giving way for VRU) • Respect towards VRU (Purpose) • Placement (lateral, direction of car, and in time) • Speed • Coming to full stop (when giving way for VRU) Perception of the AV behaviour • The perceived intelligence of the automation depended on the situations • In critical situations, Defensive mode was preferred since it more clearly communicated the intention of the car - e.g. early slow down for pedestrian • In none critical situation, Aggresive mode was preferred since it was perceived as more effective - e.g. narrow turn in roundabout 12

4/20/2018 Discussion • To communicate the intention of the car emerged as an important factor • The driving behavior communicates the intention – is the car aware of the surroundings? • Can the behavior of the car be used intentionally to communicate the intention of the car? • HMI • How to match the driving behavior to the graphical user interface? • How to sync cues from driving behavior with cues graphical in user interface? • Difference between a “Defensive” interface and a “Aggressive” interface? Conclusions • The participants related the driving behavior to car having intelligence/agency • The driving behavior affected the trust of the participants • People experienced the automated car as a whole • The vehicle dynamics and driving pattern need to be seen an essential part of user interface of the car to create trust • The whole autonomous car is the user interface to the driver/passenger 13

4/20/2018 Trust in Automated Vehicles Fredrick Ekman and Mikael Johansson ekmanfr@chalmers.se, johamik@chalmers.se Design & Human Factors, Chalmers 14